Exploration of the free energy landscapes of boron, beryllium and copper nanoclusters at finite temperature via DFT and statistical thermodynamics

Abstract

Clusters are aggregates of atoms that are too large to be called molecules and too small to resemble crystal fragments and their properties are highly dependent on structure, size, composition, and temperature; however, most theoretical studies of density functional assume that the temperature is 0 K and neglect temperaturedependent contributions as their finite-temperature properties remain virtually unexplored. Experimental studies are carried out at temperatures higher than 0 K, and it is necessary to understand the effect of temperature on the properties of the cluster and also on the determination of the lowest energetic structure at finite temperature. In this doctoral thesis, we conducted a theoretical-computational study at finite temperature of the structural, thermochemical, and electronic properties of atomic nanoclusters formed by elements of Boron, Beryllium and Copper using density functional theory and statistical thermodynamics. The knowledge of the minimum energy geometries and the most energetically unstable isomers are essential in calculating electronic, and geometric properties, which consequently provide a complete vision of the molecular system. The starting point for understanding the properties of the cluster is the putative global minimum and all lower energy structures near it; locating those low-energy structures is only the first difficult step. Combined DFT with statistical thermodynamics, we roughly calculated the relative thermal populations highly dependent on temperatura and the effect of temperature on IR spectra. To elucidate the lowest energy structure and their neighbors, we conducted an extensive and systematic global exploration of potential/free energy landscapes to locate the low-energy structures of clusters formed by B, Be, and Cu atoms. To achieve what was mentioned above, we employed a hybrid genetic algorithm, developed and implemented by our research group, written in Python and coupled to any electronic structure program available; Also, we developed the computational codes necessary for calculating the thermochemical properties.